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1045 articles for “U-net”
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Comparative Study of Facial Spoofing Detection using CNN Architecture
Abstract: Facial recognition systems face a high risk of security breach due to various facial spoofing attacks. This challenge was addressed by the study of several deep learning models. This study proposes an idea to detect facial spoofing using deep learning architecture to differentiate live faces form various types of spoofed images/videos using different CNN models. In addition, the study seeks to strengthen security measured in facial recognition system demonstrating that …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 9–17 Read article
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Next-generation Operating Systems: AI-driven Autonomy, Quantum Integration, and Edge Computing
Abstract: The rapid evolution of computing paradigms is driving the need for next-generation operating systems that seamlessly integrate artificial intelligence, quantum computing, and edge processing. Traditional operating systems, while efficient for classical computation, lack the necessary capabilities to handle real-time AI-driven decision-making, quantum processing, and decentralized edge networks. This study explores how future operating systems will incorporate AI-driven autonomy to enhance resource management, quantum integration to leverage superior computational power, and …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 25–36 Read article
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Securing Healthcare 5.0: A Review of Applications, Security Challenges, and Future Perspectives
Abstract: Healthcare 5.0 represents a revolutionary shift in the healthcare sector, focusing on individualized, patient-centric care through the integration of different cutting-edge technologies such as internet of things, artificial intelligence, big data analytics, blockchain, and cloud computing to enable healthcare services such as real-time health monitoring, personalized treatments, and access to expert advice regardless of geographic barriers. Potentially, Healthcare 5.0 supports more engaged and effective care and help through a focus …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 22–36 Read article
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Smart Polymer Composites with Multifunctional Capabilities Integrating Electroactive Polymers Conductive Nanofillers and Flexible Electronics for Advanced Sensing and Actuation Systems
Abstract: Smart polymer composites have gained significant attention to their ability to integrate polymer matrices with conductive nanofillers, offering tunable electrical, mechanical, and electroactive properties. These composites are highly responsive to external stimuli such as electrical fields, mechanical stress, and temperature variations, making them ideal for applications in flexible electronics, soft robotics, and adaptive sensing systems. This research investigates the effect of nanofiller dispersion on the performance of polymer composites, optimizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 946–965 Read article
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IoT-Enabled Polymer–Gel PCM Composites for Intelligent Thermal Management in Solar Facade Applications
Abstract: The present study investigates the development of a multifunctional polymer–gel phase change composite designed for solar façade applications with integrated real-time thermal monitoring capability. A crosslinked polyvinyl alcohol–borax matrix was employed as a three-dimensional polymer scaffold to encapsulate paraffin-based phase change material, ensuring leakage-free operation and structural integrity under repeated thermal cycling. Graphite nanoplatelets were incorporated as thermally conductive nano-fillers to enhance heat transfer through the polymer composite via percolation-driven …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 99–111 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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A Security Investigation Survey of Ransomware Detection and Avoidance Strategies for IoT Networks
Abstract: The internet of things (IoT) refers to the interconnection of a large number of distinct physical objects, which in turn makes possible a variety of services and applications. Because the IoT sector is developing at such a rapid rate, ensuring its safety ought to be a high concern. At this time, ransomware attacks constitute the biggest danger to IoT posed by cyberattacks. Ransomware is software that blocks access to or …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 14–23 Read article
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Machine-Learning-Assisted Development of Polymer-Biochar Composite Adsorbents for the Removal of Heavy Metals from Gomti River Water
Abstract: Rapid urbanization, industrial discharge, and agricultural runoff pose a significant threat to freshwater sustainability and public health. Within these ecosystems, polymer pollutants—such as microplastics, nanoplastics, synthetic fibres, and additive residues—have emerged as persistent vectors capable of adsorbing and transporting toxic heavy metals. Because these polymeric contaminants dynamically interact with conventional aquatic parameters to alter pollutant mobility and ecological risk profiles, there is an urgent need to transition from passive environmental …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 72–95 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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Critical Review on Multifunctional Polymer Composites for Weight Reduction and AI Based Battery Thermal Management in Electric Vehicles
Abstract: The rapid growth of electric vehicles (EVs) has intensified the need for advanced materials and intelligent control systems capable of improving energy efficiency, driving range, thermal safety, and overall vehicle sustainability. This paper presents a critical review of multifunctional polymer composites and artificial intelligence-based battery thermal management systems (AI-BTMS) for next-generation EV applications. Polymer composites reinforced with carbon fibers, graphene, boron nitride, nanoclays, and carbon nanotubes offer significant advantages over …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 603–619 Read article
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Arabidopsis thaliana. (L.) Heynh Multifunctional Sensor Proteins and Signaling Networks Plant Photoreceptors
Abstract: Light is a crucial environmental cue for the growth and development of plants as well as the production of photosynthetic energy. In order to recognize and process information from incoming light, plants employ sophisticated mechanisms. With the model plant Arabidopsis thaliana, five different types of photoreceptors have been found. (L.) Heynh Photoreceptors play a specialized and/or recurring role in fine-tuning many aspects of the plant's life cycle. Unlike mobile animals, …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 1, Issue 2, 2023 · pp. 08–24 Read article
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Content-based Image Retrieval: Recent Trends and Techniques
Abstract: Due to the affordability of digital devices and the accessibility of internet technologies, a vast number of multimedia databases have been established for various applications. These image databases increase the need for efficient picture retrieval search strategies that meet user requirements. When compared to other systems, the content-based image retrieval (CBIR) system is one of the most widely used systems for retrieving images from enormous databases. Much work has been …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 01–32 Read article
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Data Security in IoT
Abstract: Privacy and security are among the major Internet of Things (IoT) challenges. Improper device upgrades, lack of effective and robust security agreements, user ignorance, and popularity active device monitoring is among the challenges IoT faces. In this work, we explore the background of IoT applications and security measures, and identifying alternative security as well privacy issues, methods used to protect location components and IoT-based programs, existing security solutions, and the …
Published in Journal of Multimedia Technology & Recent Advancements Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Offloading Computation to the Cloud
Abstract: Mobile devices are increasingly relied upon for complex and resource-intensive applications such as real-time video processing, augmented reality, and machine learning. However, their limited computational power, storage capacity, and battery life pose significant challenges. Computation offloading to the cloud has emerged as a promising solution to overcome these limitations by transferring demanding tasks from mobile devices to remote cloud servers. This approach enables improved performance, reduced energy consumption, and enhanced …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 27–37 Read article
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Green and Edge-Aware Computing: Rethinking Cloud Infrastructure for Sustainability
Abstract: Cloud computing has transformed the way organizations access and manage information technology resources, providing flexible, scalable, and cost-efficient services that support today’s data-driven world. Despite these advantages, the rapid expansion of large-scale cloud infrastructures has resulted in rising energy consumption, significant heat generation, and a growing environmental footprint. This research focuses on advancing green cloud computing by examining methods that reduce power usage while maintaining high performance. Key strategies include …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 17–24 Read article
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Detection and Classification of Brain Tumor from MRI And CT Images using Harmony Search Optimization and Deep Learning
Abstract: Primary brain tumor detection and classification are critical factors in ensuring effective treatment and, ultimately, improving patient well-being. This paper describes a novel method for detecting and classifying brain tumors with the help of magnetic resonance imaging (MRI) and computed tomography (CT) images. The suggested method combines harmony search optimization (HSO) and Convolution Neural Networks (CNN) based on deep learning techniques, yielding an impressive accuracy rate of 99.13% for both …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 31–49 Read article
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Socio-Economic Impacts of Rivers State Government Ring Road Project on Residents of Port Harcourt Municipality
Abstract: As nations strive towards improving the socio-economic well-being of its citizens, efficient transportation system in the form of ring roads have become a desideratum for reducing traffic congestion and enhancing movement of goods and services. The paper examines the impacts a ring road can have on residents of project area with emphasis on Port Harcourt. The Hazard and Effect Management Process (HEMP) technique developed by SHELL was used to examine …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 1, 2025 · pp. 42–51 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article